Improving Local Search for Minimum Weighted Connected Dominating Set Problem by Inner-Layer Local Search

The minimum weighted connected dominating set (MWCDS) problem is an important variant of connected dominating set problems with wide applications, especially in heterogenous networks and gene regulatory networks. In the paper, we develop a nested local search algorithm called NestedLS for solving MWCDS on classic benchmarks and massive graphs. In this local search framework, we propose two novel ideas to make it effective by utilizing previous search information. First, we design the restart based smoothing mechanism as a diversification method to escape from local optimal. Second, we propose a novel inner-layer local search method to enlarge the candidate removal set, which can be modelled as an optimized version of spanning tree problem. Moreover, inner-layer local search method is a general method for maintaining the connectivity constraint when dealing with massive graphs. Experimental results show that NestedLS outperforms state-of-the-art meta-heuristic algorithms on most instances

Generating Pictorial Storylines Via Minimum-Weight Connected Dominating Set Approximation in Multi-View Graphs

This paper introduces a novel framework for generating pictorial storylines for given topics from text and image data on the Internet. Unlike traditional text summarization and timeline generation systems, the proposed framework combines text and image analysis and delivers a storyline containing textual, pictorial, and structural information to provide a sketch of the topic evolution. A key idea in the framework is the use of an approximate solution for the dominating set problem. Given a collection of topic-related objects consisting of images and their text descriptions, a weighted multi-view graph is first constructed to capture the contextual and temporal relationships among these objects. Then the objects are selected by solving the minimum-weighted connected dominating set problem defined on this graph. Comprehensive experiments on real-world data sets demonstrate the effectiveness of the proposed framework

Populating knowledge bases with temporal information

Recent progress in information extraction has enabled the automatic construction of large knowledge bases. Knowledge bases contain millions of entities (e.g. persons, organizations, events, etc.), their semantic classes, and facts about them. Knowledge bases have become a great asset for semantic search, entity linking, deep analytics, and question answering. However, a common limitation of current knowledge bases is the poor coverage of temporal knowledge. First of all, so far, knowledge bases have focused on popular events and ignored long tail events such as political scandals, local festivals, or protests. Secondly, they do not cover the textual phrases denoting events and temporal facts at all. The goal of this dissertation, thus, is to automatically populate knowledge bases with this kind of temporal knowledge. The dissertation makes the following contributions to address the afore mentioned limitations. The first contribution is a method for extracting events from news articles. The method reconciles the extracted events into canonicalized representations and organizes them into fine-grained semantic classes. The second contribution is a method for mining the textual phrases denoting the events and facts. The method infers the temporal scopes of these phrases and maps them to a knowledge base. Our experimental evaluations demonstrate that our methods yield high quality output compared to state-of- the-art approaches, and can indeed populate knowledge bases with temporal knowledge.Der Fortschritt in der Informationsextraktion ermöglicht heute das automatischen Erstellen von Wissensbasen. Derartige Wissensbasen enthalten Entitäten wie Personen, Organisationen oder Events sowie Informationen über diese und deren semantische Klasse. Automatisch generierte Wissensbasen bilden eine wesentliche Grundlage für das semantische Suchen, das Verknüpfen von Entitäten, die Textanalyse und für natürlichsprachliche Frage-Antwortsysteme. Eine Schwäche aktueller Wissensbasen ist jedoch die unzureichende Erfassung von temporalen Informationen. Wissenbasen fokussieren in erster Linie auf populäre Events und ignorieren weniger bekannnte Events wie z.B. politische Skandale, lokale Veranstaltungen oder Demonstrationen. Zudem werden Textphrasen zur Bezeichung von Events und temporalen Fakten nicht erfasst. Ziel der vorliegenden Arbeit ist es, Methoden zu entwickeln, die temporales Wissen au- tomatisch in Wissensbasen integrieren. Dazu leistet die Dissertation folgende Beiträge: 1. Die Entwicklung einer Methode zur Extrahierung von Events aus Nachrichtenartikeln sowie deren Darstellung in einer kanonischen Form und ihrer Einordnung in detaillierte semantische Klassen. 2. Die Entwicklung einer Methode zur Gewinnung von Textphrasen, die Events und Fakten in Wissensbasen bezeichnen sowie einer Methode zur Ableitung ihres zeitlichen Verlaufs und ihrer Dauer. Unsere Experimente belegen, dass die von uns entwickelten Methoden zu qualitativ deutlich besseren Ausgabewerten führen als bisherige Verfahren und Wissensbasen tatsächlich um temporales Wissen erweitern können

Of memories and ripples

The hippocampus is one of the regions in the mammalian brain that is associated with memory of events in their spatiotemporal context. Sequences of neuronal activity in the hippocampus are the chief candidate for a neurophysiological correlate of such contextual, or episodic memory. Simultaneously to replaying these behaviorally-related activity sequences, the hippocampus engages in a powerful and fast oscillation known as sharp-wave ripples (SWR). Ripples in turn participate in a brain-wide pattern of activity and may orchestrate the local strengthening of memories and their broadcasting to the cortex. In this Thesis, both memory sequences and ripple oscillations are studied in the light of the unifying hypothesis that the coordinated activation of a neuronal assembly represents an individual memory item in the sequences, and is at the same time responsible for the individual cycles in the oscillations. To test the hypothesis, we investigated SWR in vitro and in vivo in the mouse, using intracellular recordings of currents in CA1 pyramidal cells referenced to the local field potential. Expanding current hypotheses on SWR generation, we found powerful, well ripple-locked and spatially pervasive but CA1-local excitatory inputs, indicative of presynaptic assemblies of CA1 principal neurons. Combining a novel peeling reconstruction algorithm for synaptic currents with recordings at different holding potentials, we could for the first time unravel individual synaptic contributions during ripples. Analysis of the strikingly precise timing of currents demonstrated that inhibition aligns its phase to excitation over the course of a ripple. We carried on the dissection of ripples to the theoretical domain by incorporating the effect of inhibition into a mean field model of sequence replay. Using this model, we inquired what are the neuronal assembly size and inhibitory feedback strength that maximize the capacity of a hippocampal network to store memories, so that those memories can be successfully retrieved during ripple episodes. We found that a linearly coupled inhibitory population indeed helps increase storage capacity by dynamically stabilizing replay in an oscillatory manner for lower assembly sizes than in absence of inhibition. The findings about the temporal structure of neuronal activation during ripples complement our experimental observations. Collectively, they offer new insights on the physiology and function of sharp-wave ripples, paving the way for an integrated, continuous-time model of large networks of sparsely connected neurons that replay activity sequences concomitant to transient ensemble oscillations

Metropolitan Research: Methods and Approaches

Metropolitan research requires multidisciplinary perspectives in order to do justice to the complexities of metropolitan regions. This volume provides a scholarly and accessible overview of key methods and approaches in metropolitan research from a uniquely broad range of disciplines including architectural history, art history, heritage conservation, literary and cultural studies, spatial planning and planning theory, geoinformatics, urban sociology, economic geography, operations research, technology studies, transport planning, aquatic ecosystems research and urban epidemiology. It is this scope of disciplinary - and increasingly also interdisciplinary - approaches that allows metropolitan research to address recent societal challenges of urban life, such as mobility, health, diversity or sustainability

Metropolitan Research

Metropolitan research requires multidisciplinary perspectives in order to do justice to the complexities of metropolitan regions. This volume provides a scholarly and accessible overview of key methods and approaches in metropolitan research from a uniquely broad range of disciplines including architectural history, art history, heritage conservation, literary and cultural studies, spatial planning and planning theory, geoinformatics, urban sociology, economic geography, operations research, technology studies, transport planning, aquatic ecosystems research and urban epidemiology. It is this scope of disciplinary - and increasingly also interdisciplinary - approaches that allows metropolitan research to address recent societal challenges of urban life, such as mobility, health, diversity or sustainability

Metropolitan Research

Metropolitan research requires multidisciplinary perspectives in order to do justice to the complexities of metropolitan regions. This volume provides a scholarly and accessible overview of key methods and approaches in metropolitan research from a uniquely broad range of disciplines including architectural history, art history, heritage conservation, literary and cultural studies, spatial planning and planning theory, geoinformatics, urban sociology, economic geography, operations research, technology studies, transport planning, aquatic ecosystems research and urban epidemiology. It is this scope of disciplinary - and increasingly also interdisciplinary - approaches that allows metropolitan research to address recent societal challenges of urban life, such as mobility, health, diversity or sustainability